docstr: Args:
      index (int): Index
  
  Returns:
      tuple: (image, target) where target is the image segmentation.
docstr_tok: ["Args",":","index","(","int",")",":","Index","Returns",":","tuple",":","(","image",",","target",")","where","target","is","the","image","segmentation","."]
code: def __getitem__(self, index):
      """
      Args:
          index (int): Index
  
      Returns:
          tuple: (image, target) where target is the image segmentation.
      """
      img = Image.open(self.images[index]).convert("RGB")
      target = Image.open(self.masks[index])
  
      if self.transforms is not None:
          img, target = self.transforms(img, target)
  
      return img, target
  
file_path: deep-learning-for-image-processing/pytorch_segmentation/fcn/my_dataset.py
imports: import os
  import torch.utils.data
  from PIL import Image
label_desc: Use image node_id 2 for calling the VOCSegmentation obj's underlying member method code with example usage: obj.__getitem__(index) and returns: img,  target